Sahajbert NCC

🚀 sahajBERT News Article Classification

A fine - tuned model for classifying Bengali news articles into multiple categories

✨ Features

• Collaborative: Facilitates collaborative efforts in Bengali news article classification.
• Bengali Support: Specifically designed for Bengali language news articles.
• Sequence Classification: Capable of classifying news articles into different classes.

📦 Installation

The README does not provide specific installation steps, so this section is skipped.

💻 Usage Examples

Basic Usage

You can use this model directly with a pipeline for Sequence Classification:

from transformers import AlbertForSequenceClassification, TextClassificationPipeline, PreTrainedTokenizerFast

# Initialize tokenizer
tokenizer = PreTrainedTokenizerFast.from_pretrained("neuropark/sahajBERT-NCC")

# Initialize model
model = AlbertForSequenceClassification.from_pretrained("neuropark/sahajBERT-NCC")

# Initialize pipeline
pipeline = TextClassificationPipeline(tokenizer=tokenizer, model=model)

raw_text = "এই ইউনিয়নে ৩ টি মৌজা ও ১০ টি গ্রাম আছে ।" # Change me
output = pipeline(raw_text)

📚 Documentation

Model description

sahajBERT is fine - tuned for news article classification using the sna.bn split of IndicGlue.

The model is trained for classifying articles into 5 different classes:

Intended uses & limitations

How to use

The usage example is provided in the "💻 Usage Examples" section.

Limitations and bias

WIP

Training data

The model was initialized with pre - trained weights of sahajBERT at step 19519 and trained on the sna.bn split of IndicGlue.

Training procedure

Coming soon!

Eval results

BibTeX entry and citation info

Coming soon!

📄 License

This project is licensed under the Apache 2.0 license.